6 Ways to Use Location Analytics Data in Retail Design

Hyperlocal vendors that offer location analytics tools are changing the way the in-store shopping experience looks and feels, providing retailers of all sizes with the answers to questions like where customers are going in their stores, which promotions or displays are attracting the most attention, and which departments are being bypassed altogether.

According to a retail industry survey by Brickstream, 61% of retailers expect to have in-store WiFi by 2015, with department stores, supermarkets, and electronics retailers showing the most interest in using location analytics solutions to guide their marketing decisions. Here are six ways that retailers can use location analytics to organize their stores in a way that promotes as much spending as possible.

1. Measure the performance of single sales areas. “Knowing when, where, and how a customer goes through the shopping venue, with heat maps and individual motion tracking, is powerful knowledge for retailers. Retailers can measure the performance of single sales areas and eliminate inefficiencies. Some areas might attract less attention, but an adjustment of shelf positioning or staff distribution might increase conversion rates and time spent inside the shop.” (Florian Freitag, indoo.rs)

2. Improve navigation. “Creating a convenient way to shop by making it easy for a shopper to navigate a store is somewhat like making an ecommerce website easy to navigate. If shoppers know they can easily find what they want, they come back more often. With the ability to digitally suggest products to shoppers based on their location and intent leads to higher redemption and basket size, whether it’s online or in-store.” (Nathan Pettyjohn, aisle411)

3. Test flows. “Good retail design presents a store’s physical space in the optimal way to drive sales and increase brand awareness. Testing the efficacy of a design has previously been the product of trial and error. However, with new opt-in location analytics, pedestrian flow can be easily observed and quickly iterated upon to achieve an optimal design.” (Lise Murphy, Wifarer)

4. Personalize the shopping experience. “Achieving an enhanced level of personalization is the key to driving the sort of increased engagement, repeat visits, and mobile influenced in-store sales that retailers are seeking. Point Inside’s StoreMode platform ingests and synthesizes our retailer partner’s disparate enterprise data to create personalized shopper engagement opportunities that are informed by the accurate physical context of each shopper and store. It starts with answering the fundamental retail questions—Do you have it? Where can I find it? —and extends into offering up store-specific search results and recommendations that are helpful to shoppers who are using their mobile devices during their path toward an in-store purchase.” (Pete Coleman, Point Inside)

5. Understand repeat customers. “With opt-in location analytics, repeat customers can be quickly identified prior to their arrival at the POS. This allows a store to create a unique, localized and personalized experience for the consumer thereby building brand awareness and trust to increase time in the store and sales.” (Lise Murphy, Wifarer)

6. Combine location with enterprise data. “By mashing up shoppers’ behaviors with merchandising, store operations, marketing, and space planning data sources, StoreMode creates fresh mounds of data about a retailer’s in-store environment. This new data leads to improved retail execution by aligning headquarters, distribution centers, and the stores around a single source of ‘ground truth.’ Innovative visualizations then assist retailers in optimizing their footprints and assortments into what we call the ‘better box.’ This new level of insight is becoming even more essential as brick-and-mortar retailers start to rollout flexible fulfillment programs to better position themselves against their online rivals.” (Pete Coleman, Point Inside)